SUMMARY Acute pain, usually triggered by tissue injury, such as trauma or surgery, can lead to long-term persistent chronic pain, a debilitating condition that requires extensive treatment and pain management. Interestingly, the molecular basis of this transition from acute to chronic pain is poorly understood, and this lack of knowledge impedes the development of better treatment strategies for patients with chronic pain. Several recent studies have begun to explore underlying genetic and molecular signatures of the conversion to chronic pain, but clearly, additional efforts are needed to better understand the mechanisms and molecular signatures in a wider range of surgery and trauma patients. The goal of the NIH Acute to Chronic Pain Signatures (A2CPS) program is to determine the mechanisms that make some people susceptible and others resilient to the development of chronic pain. We propose an Omics Data Generation Center (ODGC) for the A2CPS Consortium as a collaborative effort of three academic institutions with complementary technical expertise, experience in large-scale data generation projects, and established collaborations and interactions: Wake Forest University Health Sciences (WFUHS), The University of California at Davis (UCD), and Duke University School of Medicine (Duke). The ODGC will generate omics data for blood samples collected from study participants at three clinical assessments (0, 3, and 6 months after a surgical procedure or musculoskeletal trauma) for an integrated analysis to identify biomarker signatures that are predictive of the transition from acute to chronic pain, and help reveal the underlying pathophysiological mechanisms mediating this transition. We have assembled a team of scientists that will use cutting-edge technologies to perform high-throughput analyses in 1) proteomics (WFUHS and Duke), 2) metabolomics (WFUHS and UCD), 3) lipidomics (UCD), 4) extracellular RNA (WFUHS), and 5) SNP genotyping (WFUHS). In addition, we propose to examine the epigenetics (DNA methylation) of monocytes collected from a subset of converters and non-converters. The resulting data will be integrated with extensive clinical assessment data, in collaboration with the Data Integration and Resource Center and the Multisite Clinical Centers of the A2CPS Consortium.